Abstract: Aspects of the disclosure relate to resource allocation and rebating during in-flight data masking and on-demand encryption of big data on a network. Computer machine(s), cluster managers, nodes, and/or multilevel platforms can request, receive, and/or authenticate requests for a big data dataset, containing sensitive and non-sensitive data. Profiles can be auto provisioned, and access rights can be assigned. Server configuration and data connection properties can be defined. Secure connection(s) to the data store can be established. Sensitive information can be redacted into a sanitized dataset based on one or more data obfuscation types. RAM requirements and current RAM allocation can be diagnosed. Portion(s) of the current RAM allocation exceeding the RAM requirements can be rebated. The encrypted data can be transmitted, in response to the request, to a source, a target, and/or another computer machine and can be decrypted back into the sanitized dataset.

Abstract: Apparatus and methods are provided for an autonomous bot that learns from user activity. The bot then autonomously acts to complete tasks that the user typically performs. The bot may detect and act in response to detecting a problem with an application. The bot may dynamically generate guidance that assists the user completing a target task. Illustrative guidance may include highlighting differences between software applications, identifying information missing from a document or form and demonstrating how to obtain the needed information or complete a task.

Abstract: A method triggers a user-definable emergency response in a voice-command based authentication system. The method receives gestures on a mobile device, and provides an interface at the mobile device to trigger an automatic interaction with an artificial intelligence (“AI”) engine stored on the mobile device. The AI accesses a database for storing legacy information associated with the caller and runs an application program interface that provides the AI engine access to the legacy information. The AI engine receives the gestures generated by the caller, accesses the database storing legacy information generated by the caller and constructs an emergency profile of the caller. The emergency profile may be based on the legacy information, a machine learning model; and/or a user training session that initializes an emergency response signal threshold level. When the gestures exceed the emergency response signal threshold level, the method may generate the emergency response.

Abstract: Embodiments of the present invention provide a secure edge device for contactless resource distribution and resource crediting from an automobile. In this way, the edge device may be affixed to or embedded within the side or the mirror of an automobile and be able to communicate with a third party device using near field communication. Upon authentication of a user, the edge device may communicate with the third party to transmit and present data about the resource distribution to the automobile display. The system allows for the user to select the resource distribution via the automobile display and provide a completion of resource distributions.

Abstract: Systems, computer program products, and methods are described herein for selective data routing in a distributed network via data throughput analysis in a distributed ledger network. The present invention is configured to receive a request for a data transmission from an endpoint device of a network, determine, via a routing module, a throughput of data associated with the data transmission, determine a classification of the data transmission, and assign the data transmission to an assigned routing channel. The assigned routing channel may include either a first routing channel or a second routing channel based on the classification, wherein the first routing channel is a light load network comprising emitter devices operatively coupled to endpoint devices proximate the emitter devices, and wherein the second routing channel is a heavy load network comprising a first multicore optical fiber.

Abstract: Systems, methods, and computer program products are provided herein for centralized data governance within distributed component computing environments. An example method includes receiving first component metadata associated with one or more operating parameters of the first distributed computing component and second component metadata associated with one or more operating parameters of the second distributed computing component. The method includes determining, via a machine learning (ML) subsystem, a centralized governance dataset based upon the first component metadata and the second component metadata. The method further includes generating a representation of the centralized governance dataset that is accessible by one or more of the first distributed computing component or the second distributed computing component.

Abstract: A system for providing a reflexively routed funds transfer is provided. The system includes a processor, and a receiver for receiving a request for a person-to-person value transfer. The request includes a request identifier. The system also includes a transmitter for transmitting the request to a shared database and a shared database. The database operates in combination with the processor to determine whether multiple targets are associated with the request identifier. When multiple targets are associated with the request identifier, the shared database operates in combination with the processor and the transmitter to notify the transfer initiator that multiple targets are associated with the request identifier, then prompts the transfer initiator to select one of the multiple targets to function as a recipient target for the value transfer. The receiver then receives a selection of one of the multiple targets to function as the recipient target. Then a router routes value transfer to the recipient target.

Abstract: A system is provided for implementing technology infrastructure upgrades using an automated electronic data aggregation tool. In particular, the system may receive a request from an endpoint device to generate a technology remediation framework for remediating a technology infrastructure issue. In response to the request, the system may use an automated electronic data aggregation tool to receive data associated with the technology infrastructure issue from one or more data sources. The system may then automatically generate the technology remediation framework using the received data and present the framework to one or more users associated with the technology infrastructure issue. In this way, the system provides an efficient way to implement upgrades and remediate issues within a technology infrastructure.

Abstract: Systems, computer program products, and methods are described herein for tracking cross border data transmissions and generating a data passport entry in an electronic network. The present disclosure is configured to receive a file, the file comprising file data; receive an origination location identifier and destination location identifier of the file; parse the file data and apply a natural language processor to the file data to generate a structured meaning of the file data; compare the structured meaning of the file data to a theme database to generate a file theme score; determine, based on the destination location identifier, a destination theme score; generate a hash value for the file; and generate a data passport entry for the file based on the file name, the origination location identifier, the destination location identifier, the file theme score, the destination theme score, the hash value, and a count score.

Abstract: A method for consolidating backup status data associated with backup operations performed at a specialty backup service platform into a centralized backup service platform may be provided. The method may include receiving data feeds associated with each backup operation, each data feed comprising backup status data associated with a backup operation performed at the specialty backup service platform. The method may also include extracting the backup status data from each data feed and following the extracting, conforming the backup status data at the centralized backup service platform to be consistent with the standardized format. The method may also include for each data feed received from the specialty backup service platform, running a performance-scan on the backup status data within the data feed for determining whether the backup operation was a success or a failure.

Abstract: Aspects of the disclosure relate to use of supervised, unsupervised, semi-supervised, or reinforcement-based machine learning algorithm(s) to perform pattern recognition and/or cluster detection on historical transactional data in order to predict events that may occur in the future and are candidates for automated delivery of items from a source to a customer in a contactless manner, via a secure delivery device, to minimize health risk(s) to the customer. The items may be securely delivered in an automated manner such as, for example, by use of a drone or autonomous vehicle, which may have advanced sensors to facilitate various aspects of the delivery. The items may be contained in a secure carrier coupled to the delivery device and may be unlocked locally or remotely using mechanical or digital means. Novel logical systems, architectures, machines, platforms, delivery devices and components thereof, and methods are disclosed.

Abstract: A device configured to identify a file in a network device, to generate a first set of block hash codes for data blocks for a first instance of the file, and to generate a second set of block hash codes for data blocks for a second instance of the file. The device is further configured to determine the first set of block hash codes matches the second set of block hash codes and to generate an entry in a file list for the instances of the file. The device is further configured to count the number of entries that are associated with the file and to determine the number of entries is greater than the redundancy threshold value. The device is further configured to delete one or more instances of the file in response to determining that the number of entries is greater than the redundancy threshold value.

Abstract: Systems for contactless authentication and event processing are provided. In some examples, a user may request processing of an event. The user may provide user identifying or event identifying information that may be transmitted to contactless processing computing platform. Based on the user identifying information, additional user data may be retrieved. An interactive authentication request may be generated and transmitted to the user computing device. The interactive authentication request may include a request for one or more types of authentication data. The user may input authentication response data into the user computing device, which may then be transmitted to the contactless processing computing platform for evaluation. The authentication response data may be evaluated to determine whether it includes a trigger, whether it matches pre-stored authentication data, and the like. In response, one or more authentication outputs may be generated and/or the requested event may be processed or denied.

Abstract: Aspects of the disclosure relate to resource allocation and rebating during in-flight data masking and on-demand encryption of big data on a network. Computer machine(s), cluster managers, nodes, and/or multilevel platforms can request, receive, and/or authenticate requests for a big data dataset, containing sensitive and non-sensitive data. Profiles can be auto provisioned, and access rights can be assigned. Server configuration and data connection properties can be defined. Secure connection(s) to the data store can be established. Sensitive information can be redacted into a sanitized dataset based on one or more data obfuscation types. RAM requirements and current RAM allocation can be diagnosed. Portion(s) of the current RAM allocation exceeding the RAM requirements can be rebated. The encrypted data can be transmitted, in response to the request, to a source, a target, and/or another computer machine and can be decrypted back into the sanitized dataset.

Abstract: A system access a blockchain network and conducts a blockchain transaction on a task log in the blockchain network. The system stores the blockchain transaction in a blockchain ledger. The system determines whether the blockchain transaction is associated with an anomaly. The anomaly indicates that the result of the blockchain transaction is unexpected. If it is determined that the blockchain transaction is associated with an anomaly, the blockchain transaction is rejected and removed from the blockchain ledger. Otherwise, the blockchain ledger is updated to indicate that the blockchain transaction is not associated with an anomaly.

Abstract: A system accesses a task log comprising text that is confidential information. The system selects a first portion of the task log. The system compares each word in the first portion with keywords that are known to be confidential information. The system determines that a word in the first portion is among the keywords. The system determines a hierarchical relationship between the word and neighboring words. The system determines that the word is associated with the neighboring words based on the hierarchical relationship. The system generates a template pattern comprising the word and one or more words associated with the word. The system obfuscates the template pattern.

Abstract: A system accesses historical tasks. The system determines historical memory resources used to execute each historical task. the historical memory resources are associated with memory categories. The system determines total historical memory resources allocated for each memory category. The system determines memory resource utilization in executing each historical task. The system determines that the memory resource utilization is not optimal. In response, the system determines a memory resource configuration that yields memory resource utilization more than a threshold percentage. The system configures network nodes according to the determined memory resource configuration to execute tasks.

Abstract: A device configured to identify a file in a network device, to generate a first set of block hash codes for data blocks for a first instance of the file, and to generate a second set of block hash codes for data blocks for a second instance of the file. The device is further configured to determine the first set of block hash codes matches the second set of block hash codes and to generate an entry in a file list for the instances of the file. The device is further configured to count the number of entries that are associated with the file and to determine the number of entries is greater than the redundancy threshold value. The device is further configured to delete one or more instances of the file in response to determining that the number of entries is greater than the redundancy threshold value.

Abstract: Aspects of the disclosure relate to detecting usage issues on enterprise systems and dynamically providing user assistance. In some embodiments, a computing platform may receive, from an automated teller system, user presence information indicating that a user has been detected at an automated teller machine associated with the automated teller system. Subsequently, the computing platform may identify, based on the user presence information received from the automated teller system, that the user has a need for assistance with the automated teller machine associated with the automated teller system. In response to identifying that the user has the need for assistance, the computing platform may generate and send one or more commands directing the automated teller machine associated with the automated teller system to execute one or more automated assistance actions corresponding to the need for assistance.

Abstract: A system is provided for implementing a data processing transaction for a home processor located within a home region. The system is configured to receive a query from a user device of a user, search a list of partner processors located within a foreign region based on the query and transmit to the user device information relating to one or more partner processors determined as a result of the search. The system receives a request to authenticate the data processing transaction at a selected partner processor, verifies an identity of the user based on the request and transmits an indication of successful authentication. The system transmits at least a portion of data relating to a registration of the user at the home processor to the selected partner processor, wherein the data processing transaction is processed by the partner processor based on the transferred data.